An Economic Assessment of Hybrid Renewable Energy for a Remote Area Electrification in Iran

2016 ◽  
Vol 818 ◽  
pp. 151-155
Author(s):  
Amir Hesam Khavari ◽  
Zulkurnain Abdul-Malek ◽  
Mehdi Moradi ◽  
Jalal Tavalaei ◽  
Sajjad Abdolahzadeh Anbaran ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Hybrid System ◽  
Fossil Fuels ◽  
Energy System ◽  
Remote Area ◽  
Energy Resources ◽  
Renewable Energy Resources ◽  
Hybrid Renewable Energy System ◽  
Hybrid Renewable Energy ◽  
The Impact

The utilization of renewable resources is growing, in part due to the environmental impacts caused by fossil fuels. The largest sources of renewable energy are wind and solar and many predict that these energy sources will be increasingly used for distributed generation. In this paper, the feasibility is examined of a grid-independent system applied for a remote area electrification in Binalood, Iran. Traditional power systems for remote or rural areas are based on fossil fuels. After addition of renewable energy resources, solar energy applications have become popular in remote energy systems. The recent study and research works show that adding other possible renewable energy resources such as wind, hydro and biomass could make a hybrid system more cost-effective and environmentally friendly. Hence, in the present study, an overview of applied hybrid renewable energy system (HRES) for worldwide villages with special attention on Iran has been proposed to help present and future works for better achievement in this field. Furthermore sensitivity analyses are performed to determine the impact on performance of several key parameters: wind speed and fuel costs. HOMER was used to evaluate the feasibility of various hybrid systems. The results of a comprehensive feasibility data analysis along with its economic evaluation indicate that the wind-diesel hybrid system with battery storage is most efficient energy system for supplying this remote area's electrical energy demands.

scholarly journals A preliminary stochastic analysis of the uncertainty of natural processes related to renewable energy resources

2018 ◽  
Vol 45 ◽  
pp. 193-199
Author(s):  
Elli Klousakou ◽  
Maria Chalakatevaki ◽  
Panayiotis Dimitriadis ◽  
Theano Iliopoulou ◽  
Romanos Ioannidis ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Stochastic Analysis ◽  
Energy Demand ◽  
Fossil Fuels ◽  
Energy System ◽  
Energy Resources ◽  
Hurst Parameter ◽  
Renewable Energy Resources ◽  
Hybrid Renewable Energy System ◽  
Geophysical Processes

Abstract. The ever-increasing energy demand has led to overexploitation of fossil fuels deposits, while renewables offer a viable alternative. Since renewable energy resources derive from phenomena related to either atmospheric or geophysical processes, unpredictability is inherent to renewable energy systems. An innovative and simple stochastic tool, the climacogram, was chosen to explore the degree of unpredictability. By applying the climacogram across the related timeseries and spatial-series it was feasible to identify the degree of unpredictability in each process through the Hurst parameter, an index that quantifies the level of uncertainty. All examined processes display a Hurst parameter larger than 0.5, indicating increased uncertainty on the long term. This implies that only through stochastic analysis may renewable energy resources be reliably manageable and cost efficient. In this context, a pilot application of a hybrid renewable energy system in the Greek island of Astypalaia is discussed, for which we show how the uncertainty (in terms of variability) of the input hydrometeorological processes alters the uncertainty of the output energy values.

Optimum sizing and simulation of hybrid renewable energy system for remote area

2021 ◽  
pp. 0958305X2110301
Author(s):  
Animesh Masih ◽  
HK Verma
Keyword(s):  
Renewable Energy ◽  
Reliability Index ◽  
Energy System ◽  
Energy Resources ◽  
Total System ◽  
Renewable Energy Resources ◽  
Optimal Sizing ◽  
Remote Areas ◽  
Grasshopper Optimization Algorithm ◽  
Hybrid Renewable Energy

In current scenario, people tend to move towards outskirts and like to settle in places that are close to nature. But, due to urban lifestyle and to fulfill the basic needs, demand of electricity remains the same as in urban areas. This demand of electricity can be only fulfilled by using hybrid renewable energy resources, which is easily available in outskirts. Renewable energy resources are unreliable and more expensive. Researchers are working to make, it more reliable and economic in terms of utilization. This article proposes a metaheuristic grasshopper optimization algorithm (GOA) for the optimal sizing of hybrid PV/wind/battery energy system located in remote areas. The proposed algorithm finds the optimal sizing and configuration of remote village load demand that includes house electricity and agriculture. The optimization problem is solved by minimization of total system cost at a desirable level of loss of power supply’s reliability index (LPSRI). The results of GOA are compared with particle swarm optimization (PSO), genetic algorithm (GA) and hybrid optimization of multiple energy resources (HOMER) software. In addition, results are also validated by modeling and simulation of the hybrid energy system and its configurations at different weather conditions-based results. Hybrid PV/wind/battery is found as an optimal system at remote areas and sizing are[Formula: see text] with cost of energy (COE) (0.3473$/kWh) and loss of power supplies reliability index (LPSRI) (0%). It is clear from the results that GOA based methods are more efficient for selection of optimal energy system configuration as compared to others algorithms.

scholarly journals Simulation-Based Optimization of Hybrid Renewable Energy System for Off-grid Rural Electrification

2021 ◽  
Vol 10 (4) ◽  
pp. 667-686
Author(s):  
Akinola Sunday Oladeji ◽  
Mudathir Funsho Akorede ◽  
Salihu Aliyu ◽  
Abdulrasaq Apalando Mohammed ◽  
Adebayo Wahab Salami
Keyword(s):  
Renewable Energy ◽  
Rural Areas ◽  
Energy System ◽  
Renewable Energy Resources ◽  
Multi Objective ◽  
Hybrid Renewable Energy System ◽  
Renewable Energy System ◽  
Simulation Based ◽  
Simulation Based Optimization ◽  
Hybrid Renewable Energy

There is a need to develop an optimization tool that can be applied in the feasibility study of a hybrid renewable energy system to find the optimal capacity of different renewable energy resources and support the decision makers in their performance investigation. A multi-objective function which minimizes the Levelized Cost of Energy (LCOE) and Loss of Load Probability Index (LLPI) but maximizes the novel Energy Match Ratio (EMR) was formulated. Simulation-based optimization method combined with ε-constraint technique was developed to solve the multi-objective optimization problem. In the study, ten-year hourly electrical load demand, using the end-use model, is estimated for the communities. The performance of the developed algorithm was evaluated and validated using Hybrid Optimization Model for Electric Renewables (HOMER®) optimization software. The developed algorithm minimized the LCOE by 6.27% and LLPI by 167% when compared with the values of LCOE ($0.444/kWh) and LLPI (0.000880) obtained from the HOMER® optimization tool. Also, the LCOE with the proposed approach was calculated at $0.417/kWh, which is lower than the $0.444/kWh obtained from HOMER®. From environmental perspective, it is found that while 141,370.66 kg of CO2 is saved in the base year, 183,206.51 kg of CO2 is saved in the ninth year.The study concluded that the approach is computationally efficient and performed better than HOMER® for this particular problem.The proposed approach could be adopted for carrying out feasibility studies and design of HRES for Off-Grid electrification, especially in the rural areas where access to the grid electricity is limited

scholarly journals Design and Analysis of In-Pipe Hydro-Turbine for an Optimized Nearly Zero Energy Building

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8154
Author(s):  
Muhammad Shahbaz Aziz ◽  
Muhammad Adil Khan ◽  
Harun Jamil ◽  
Faisal Jamil ◽  
Alexander Chursin ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Vertical Channel ◽  
Energy System ◽  
Hydroelectric Power ◽  
Renewable Energy Resources ◽  
Zero Energy ◽  
Ansys Fluent ◽  
Zero Energy Building ◽  
Hybrid Renewable Energy System ◽  
Hybrid Renewable Energy

Pakistan receives Direct Normal Irradiation (DNI) exceeding 2000 kWh/m²/annum on approximately 83% of its land, which is very suitable for photovoltaic production. This energy can be easily utilized in conjunction with other renewable energy resources to meet the energy demands and reduce the carbon footprint of the country. In this research, a hybrid renewable energy solution based on a nearly Zero Energy Building (nZEB) model is proposed for a university facility. The building in consideration has a continuous flow of water through its water delivery vertical pipelines. A horizontal-axis spherical helical turbine is designed in SolidWorks and is analyzed through a computational fluid dynamics (CFD) analysis in ANSYS Fluent 18.1 based on the K-epsilon turbulent model. Results obtained from ANSYS Fluent have shown that a 24 feet vertical channel with a water flow of 0.2309 m3/s and velocity of 12.66 m/s can run the designed hydroelectric turbine, delivering 168 W of mechanical power at 250 r.p.m. Based on the turbine, a hybrid renewable energy system (HRES) comprising photovoltaic and hydroelectric power is modelled and analyzed in HOMER Pro software. Among different architectures, it was found that architecture with hydroelectric and photovoltaic energy provided the best COE of $0.09418.

scholarly journals Control Strategy of a Hybrid Renewable Energy System Based on Reinforcement Learning Approach for an Isolated Microgrid

2019 ◽  
Vol 9 (19) ◽  
pp. 4001 ◽  
Author(s):  
Phan ◽  
Lai
Keyword(s):  
Renewable Energy ◽  
Reinforcement Learning ◽  
Energy System ◽  
The Philippines ◽  
Energy Resources ◽  
Hydrogen Energy ◽  
Optimal Sizing ◽  
Hybrid Renewable Energy System ◽  
Renewable Energy System ◽  
Hybrid Renewable Energy

Due to the rising cost of fossil fuels and environmental pollution, renewable energy (RE) resources are currently being used as alternatives. To reduce the high dependence of RE resources on the change of weather conditions, a hybrid renewable energy system (HRES) is introduced in this research, especially for an isolated microgrid. In HRES, solar and wind energies are the primary energy resources while the battery and fuel cells (FCs) are considered as the storage systems that supply energy in case of insufficiency. Moreover, a diesel generator is adopted as a back-up system to fulfill the load demand in the event of a power shortage. This study focuses on the development of HRES with the combination of battery and hydrogen FCs. Three major parts were considered including optimal sizing, maximum power point tracking (MPPT) control, and the energy management system (EMS). Recent developments and achievements in the fields of machine learning (ML) and reinforcement learning (RL) have led to new challenges and opportunities for HRES development. Firstly, the optimal sizing of the hybrid renewable hydrogen energy system was defined based on the Hybrid Optimization Model for Multiple Energy Resources (HOMER) software for the case study in an island in the Philippines. According to the assessment of EMS and MPPT control of HRES, it can be concluded that RL is one of the most emerging optimal control solutions. Finally, a hybrid perturbation and observation (P&O) and Q-learning (h-POQL) MPPT was proposed for a photovoltaic (PV) system. It was conducted and validated through the simulation in MATLAB/Simulink. The results show that it showed better performance in comparison to the P&O method.

scholarly journals Optimum Design of Hybrid Renewable Energy System for Sustainable Energy Supply to a Remote Island

2020 ◽  
Vol 12 (3) ◽  
pp. 1280 ◽  
Author(s):  
Sajid Ali ◽  
Choon-Man Jang
Keyword(s):  
Renewable Energy ◽  
Optimum Design ◽  
Peak Load ◽  
Ghg Emissions ◽  
Energy System ◽  
Hybrid Renewable Energy System ◽  
Renewable Energy System ◽  
Remote Island ◽  
Hybrid Renewable Energy ◽  
The Impact

Renewable energy technologies can not only help in mitigating the greenhouse gas (GHG) emissions but it can also be very useful for electricity generation at remote locations, where no other means of power are available. The present study focuses on the techno-economic optimum design of a small hybrid renewable energy system (HRES) consisting of wind-solar as primary energy sources. The HRES was modelled for a remote island (Deokjeok-do Island, South Korea) using real electricity consumption data for one complete year. A daily mean load of 24,720 kWh was entered at Deokjeok-do Island with a peak load of 2291.54 kW. Average annual values of wind speed and daily solar radiations were estimated to be 3.6 m/s (10 m height) and 4.13 kWh/m2, respectively. A total of 8760 simulations were performed to achieve the hourly load demand of the mentioned island. In order to deal with the surplus and electricity deficit, two different types of energy storage systems (ESS) were modelled i.e., battery and pumped hydro storage (PHS). Four different HRESs were also evaluated as the most suitable based on levelized cost of energy (LCOE) and net present cost (NPC). A detailed economic break-down of each component and the impact of different sensitivity variables on decision making have also been discussed in detail.

scholarly journals Techno-Economic Analysis of a Stand-Alone Hybrid System: Application in Donoussa Island, Greece

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1868
Author(s):  
Michail Katsivelakis ◽  
Dimitrios Bargiotas ◽  
Aspassia Daskalopulu ◽  
Ioannis P. Panapakidis ◽  
Lefteri Tsoukalas
Keyword(s):  
Renewable Energy ◽  
Economic Analysis ◽  
Hybrid System ◽  
Renewable Energy Sources ◽  
Energy System ◽  
Hybrid Renewable Energy Systems ◽  
Hybrid Renewable Energy System ◽  
Cost Of Energy ◽  
System Configurations ◽  
Hybrid Renewable Energy

Hybrid Renewable Energy Systems (HRES) are an attractive solution for the supply of electricity in remote areas like islands and communities where grid extension is difficult. Hybrid systems combine renewable energy sources with conventional units and battery storage in order to provide energy in an off-grid or on-grid system. The purpose of this study is to examine the techno-economical feasibility and viability of a hybrid system in Donoussa island, Greece, in different scenarios. A techno-economic analysis was conducted for a hybrid renewable energy system in three scenarios with different percentages of adoption rate (20%, 50% and 100%)and with different system configurations. Using HOMER Pro software the optimal system configuration between the feasible configurations of each scenario was selected, based on lowest Net Present Cost (NPC), minimum Excess Electricity percentage, and Levelized Cost of Energy (LCoE). The results obtained by the simulation could offer some operational references for a practical hybrid system in Donoussa island. The simulation results confirm the application of a hybrid system with 0% of Excess Electricity, reasonable NPC and LCoE and a decent amount of renewable integration.

scholarly journals Simulation-Based Optimization of Hybrid Renewable Energy System for Off-grid Rural Electrification

2021 ◽  
Vol 10 (4) ◽  
Author(s):  
Akinola Sunday Oladeji ◽  
Mudathir Funsho Akorede ◽  
Salihu Aliyu ◽  
Abdulrasaq Apalando Mohammed ◽  
Adebayo Wahab Salami
Keyword(s):  
Renewable Energy ◽  
Rural Areas ◽  
Energy System ◽  
Renewable Energy Resources ◽  
Multi Objective ◽  
Hybrid Renewable Energy System ◽  
Renewable Energy System ◽  
Simulation Based ◽  
Simulation Based Optimization ◽  
Hybrid Renewable Energy

There is a need to develop an optimization tool that can be applied in the feasibility study of a hybrid renewable energy system to find the optimal capacity of different renewable energy resources and support the decision makers in their performance investigation. A multi-objective function which minimizes the Levelized Cost of Energy (LCOE) and Loss of Load Probability Index (LLPI) but maximizes the novel Energy Match Ratio (EMR) was formulated. Simulation-based optimization method combined with ε-constraint technique was developed to solve the multi-objective optimization problem. In the study, ten-year hourly electrical load demand, using the end-use model, is estimated for the communities. The performance of the developed algorithm was evaluated and validated using Hybrid Optimization Model for Electric Renewables (HOMER®) optimization software. The developed algorithm minimized the LCOE by 6.27% and LLPI by 167% when compared with the values of LCOE ($0.444/kWh) and LLPI (0.000880) obtained from the HOMER® optimization tool. Also, the LCOE with the proposed approach was calculated at $0.417/kWh, which is lower than the $0.444/kWh obtained from HOMER®. From environmental perspective, it is found that while 141,370.66 kg of CO2 is saved in the base year, 183,206.51 kg of CO2 is saved in the ninth year.The study concluded that the approach is computationally efficient and performed better than HOMER® for this particular problem.The proposed approach could be adopted for carrying out feasibility studies and design of HRES for Off-Grid electrification, especially in the rural areas where access to the grid electricity is limited

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